linmos (Linear Mosaic Applicator)
This page provides instruction for using the linmos program. The purpose of
this software is to perform a linear mosaic of a set of images.
Running the program
It can be run with the following command, where “config.in” is a file containing
the configuration parameters described in the next section.
The linmos program is not parallel/distributed.
Parallel linmos (linmos-mpi)
There is a parallel version of linmos which will divide the mosaic over the number of
ranks. This improves the run time markedly as the I/O is distributed. Furthermore this also
reduces the memory load.
Configuration Parameters
The following table contains the configuration parameters to be specified in the config.in
file shown on above command line. Note that each parameter must be prefixed with “linmos.”.
For example, the weighttype parameter becomes linmos.weighttype.
Note
During the BETA campaign there is no default option for weighttype. This option must
be set.
| Parameter |
Type |
Default |
Description |
|---|
| names |
vector<string> |
none |
Names of the input images. If these images start with
“image” and have associated sensitivity images, the latter
are integrated into a sensitivity image for the mosaic. |
| weights |
vector<string> |
null |
Optional parameter (required if using weight images). Names
of input images containing pixel weights. There must be one
weight image for each image, and the size must match.
Ignored if weighttype=FromPrimaryBeamModel or if
findmosaics=true. |
| outname |
string |
none |
Name of the output image. Ignored if findmosaics=true. |
| outweight |
string |
none |
Name of output image containing pixel weights. Ignored if
findmosaics=true. |
| weighttype |
string |
none |
How to determine the pixel weights. Options:
- FromWeightImages: from weight images. Parameter
weights must be present and there must be a one-to-one
correspondence with the input images.
- FromPrimaryBeamModel: using a Gaussian primary-beam
model. If beam centres are not specified (see below),
the reference pixel of each input image is used.
- Combined: ** linmos-mpi only ** uses both the weight
images and the PB model to form the pixel weight
|
| weightstate |
string |
Corrected |
The weighting state of the input images.
Options:
- Corrected: Direction-dependent beams/weights have
been divided out of input images.
- Inherent: Input images retain the natural
primary-beam weighting of the visibilities.
- Weighted: Full primary-beam-squared weighting.
|
| cutoff |
float |
0.01 |
Desired cutoff of the gain function used to form weights,
relative to the maximum gain. |
| psfref |
uint |
0 |
Which of the input images to extract restoring-beam
information from. The default behaviour is to use the
first image specified (indices start at 0). |
| nterms |
uint |
-1 |
Process multiple taylor-term images. The string “taylor.0”
must be present in both input and output image names
(including weights images), and it will be incremented from
0 to nterms-1. Ignored if findmosaics=true. |
| findmosaics |
bool |
false |
Instead of specifying specific input and output files to
mosaic, search the current directory for suitable mosaics.
Parameter names is used to specify a vector of tags, and
all groups of images that have names that are equal apart
from these tags are mosaicked together. Groups must have one
image per tag. Currently only groups with prefixes of
“image” and “residual” are allowed, with prefixes “weights”
and “sensitivity” special cases that are searched for once
groups are identified. Parameters weights, outname,
outweight and nterms are ignored if findmosaic=true. |
If input images need to be regridded, the following ImageRegrid options are available:
| Parameter |
Type |
Default |
Description |
|---|
| regrid.method |
string |
linear |
ImageRegrid interpolation method: nearest, linear,
cubic or lanczos. |
| regrid.decimate |
uint |
3 |
ImageRegrid decimation factor. In the range 3-10 is likely
to provide the best performance/accuracy tradeoff |
| regrid.replicate |
bool |
false |
ImageRegrid replicate option. |
| regrid.force |
bool |
false |
ImageRegrid force option. |
Definition of beam centres
If weights are generated from primary-beam models (weighttype=FromPrimaryBeamModel), it is possible to set the
beam centres from within the parset. Since this is most likely useful when each input image comes from a different
multi-beam feed, feeds offset parameters from other applications are used for this. If the origin of the beams
offset system is not specified, using either feeds.centre or feeds.centreref, any offsets are ignored and the
reference pixel of each input image is used as the primary-beam centre.
The feeds parameters can be given either in the main linmos parset or a separate offsets parset file set by the
feeds.offsetsfile parameter.
| Parameter |
Type |
Default |
Description |
|---|
| feeds.centre |
vector<string> |
none |
Optional parameter (it or feeds.centreref required when
specifying beam offsets).
Two-element vector containing the right ascension and
declination that all of the offsets are relative to. |
| feeds.centreref |
int |
none |
Optional parameter (it or feeds.centre required when
specifying beam offsets). Which of the input images to use
to automatically set feeds.centre. Indices start at 0.
If neither of these parameters are set, the reference pixel
of each input image is used as the primary-beam centre. |
| feeds.spacing |
string |
none |
Optional parameter (required when specifying beam offsets
in the main linmos parset). Beam/feed spacing when giving
offsets in the main linmos parset. If feeds.offsetsfile
is given, this parameter will be ignored. |
| feeds.names[i]
(one per input
image) |
vector<string> |
none |
Optional parameter (required when specifying beam offsets
in the main linmos parset). Two-element vector containing
the beam offset relative to the feeds.centre parameter.
Offsets correspond to hour angle and declination.
names[i] should match the names of the input images,
given in linmos.names (see above). If feeds.offsetsfile
is given, these parameters will be ignored. |
| feeds.offsetsfile |
string |
none |
Optional parameter. Name of the optional beam/feed offsets
parset. If present, any offsets specified in the main
linmos parset will be ignored. |
| feeds.names |
vector<string> |
none |
Optional parameter (required either here or below when
specifying a beam offsets parset). The beam offsets parset
should have one line per input image, with parameter keys
(minus the feeds. prefix) specified by this parameter. If
the offsets parset also contains a names parameter, the
main linmos entry will hold, to allow a subset of beams
from a general to be chosen. |
If feed offsets are provided via an additional parset (i.e. not that one passed directly to
the linmos program), the file shall have the following format:
Note
These parameters, specified in the external file, do not require the “limos.” prefix.
| Parameter |
Type |
Default |
Description |
|---|
| feeds.names |
vector<string> |
null |
Optional parameter (required either here or above when
specifying a beam offsets parset). The beam offsets parset
should have one line per input image, with parameter keys
(minus the feeds. prefix) specified by this parameter. If
the offsets parset also contains a names parameter, the
main linmos entry will hold, to allow a subset of beams
from a general to be chosen. |
| feeds.spacing |
string |
none |
Beam/feed spacing. When using this extra offsets parset,
the spacing needs to be specified in this parset. |
| feeds.beamnames[i]
(one per input
image) |
vector<string> |
none |
Two-element vector containing the beam offset relative to
the feeds.centre parameter. Offsets correspond to hour
angle and declination. beamnames[i] should match the
names given in feeds.names* (see above). |
Alternate Primary Beam Models
It is possible to select the model that is used for the weighting. This is selected in the linmos parset by
the key “primarybeam”
| Parameter |
Type |
Default |
Description |
|---|
| primarybeam |
string |
“GaussianPB” |
Optional parameter that allows the user to select which
primary beam will be used in weighting. The parameters of
which can also be altered if required. Also supported are
MWA primary beams, via primarybeam = MWA_PB. |
Gaussian Primary Beam Options
You can choose the aperture size and scaling parameters both of the FWHM of the beam and a scaling of the exponent.
In the parfile these are sub parameters of the Primary beam type. (e.g linmos.primarybeam.GaussianPB.aperture)
The default Gaussian Primary beam is now 2 dimensional. But unless the user specifies x and w widths they just get the symmetric beam as defined by the aperture.
| Parameter |
Type |
Default |
Description |
|---|
| aperture |
double |
12 |
Aperture size in metres. |
| fwhmscaling |
double |
1.09 |
Scaling of the full width half max of the Gaussian |
| expscaling |
double |
4 log(2) |
Scaling of the primary beam exponent |
The 2 dimensional beam is governed by the following parameters.
| 2D-Parameters |
Type |
Default |
Description |
|---|
| (x/y)width |
double |
0.0 |
Angular width in rad. of the x (N-S) and y (E-W) Gaussian |
| (x/y)off |
double |
0.0 |
Angular offset from nominal beamcentre in rad., E, N are +ve |
| alpha |
double |
0.0 |
PA in rad. measured from North in an +ve RA direction |
MWA Primary Beam Options
| Parameter |
Type |
Default |
Description |
|---|
| latitude |
double |
-26.703319 deg |
Array latitude in radians |
| longitude |
double |
116.67081 deg |
Array longitude in radians |
| dipole.separation |
double |
1.10 metres |
Dipole separation |
| dipole.height |
double |
0.30 metres |
dipole hheight |
Primary Beam Corrections to the Taylor terms
The primary beam is a function of frequency. Therefore the apparent spectral index of a point source away from beam centre
will contain a contribution from the frequency dependence of the primary beam. It is possible to estimate this contribution
and remove it by scaling the Taylor term images appropriately.
Note
This is an analytic correction assuming a symmetric Gaussian beam
| Parameter |
Type |
Default |
Description |
|---|
| removebeam |
bool |
false |
Remove beam from the Taylor term images |
Examples
Example 1:
Example linmos parset to combine individual feed images from a 36-feed simulation. Weights
images are used to weight the pixels.
linmos.weighttype = FromWeightImages
linmos.names = [image_feed00..35_offset.i.dirty.restored]
linmos.weights = [weights_feed00..35_offset.i.dirty]
linmos.outname = image_mosaic.i.dirty.restored
linmos.outweight = weights_mosaic.i.dirty
Example 2:
Example linmos parset to combine the four inner-most feed images from a 36-feed observation.
Gaussian primary-beam models are used to weight the pixels. The primary-beam offsets are
provided in an external file.
linmos.weighttype = FromPrimaryBeamModel
linmos.names = [image_feed14..15.i.dirty.restored, image_feed20..21.i.dirty.restored]
linmos.outname = image_mosaic.i.dirty.restored
linmos.outweight = weights_mosaic.i.dirty
linmos.feeds.centre = [12h30m00.00, -45.00.00.00]
# specify a beam offsets file
linmos.feeds.offsetsfile = linmos_beam_offsets.in
# Specify which feeds from the "offsetsfile" (specified above) are to be used
linmos.feeds.names = [PAF36.feed14..15, PAF36.feed20..21]
Below is the linmos_beam_offsets.in file refered to in the above parameter set:
feeds.spacing = 1deg
<snip>
feeds.PAF36.feed14 = [-0.5, -0.5]
feeds.PAF36.feed15 = [-0.5, 0.5]
<snip>
feeds.PAF36.feed20 = [0.5, -0.5]
feeds.PAF36.feed21 = [0.5, 0.5]
<snip>
Example 3:
Example linmos parset to combine the four inner-most feed images from a 36-feed simulation.
The primary-beam offsets directly in the parameter set.
linmos.weighttype = FromPrimaryBeamModel
linmos.names = [image_feed14..15.i.dirty.restored, image_feed20..21.i.dirty.restored]
linmos.outname = image_mosaic.i.dirty.restored
linmos.outweight = weights_mosaic.i.dirty
linmos.feeds.centre = [12h30m00.00, -45.00.00.00]
linmos.feeds.spacing = 1deg
linmos.feeds.image_feed14.i.dirty.restored = [-0.5, -0.5]
linmos.feeds.image_feed15.i.dirty.restored = [-0.5, 0.5]
linmos.feeds.image_feed20.i.dirty.restored = [0.5, -0.5]
linmos.feeds.image_feed21.i.dirty.restored = [0.5, 0.5]
Example 4:
Example linmos parset to combine individual feed images from a 36-feed simulation for each of three
separate taylor terms 0, 1 and 2. The location of taylor.* in all inputs and outputs is given explicitly.
linmos.weighttype = FromWeightImages
linmos.names = [image_feed00..35_offset.i.dirty.taylor.0.restored]
linmos.weights = [weights_feed00..35_offset.i.dirty.taylor.0]
linmos.outname = image_mosaic.i.dirty.taylor.0.restored
linmos.outweight = weights_mosaic.i.dirty.taylor.0
linmos.nterms = 3
Example 5:
Example linmos parset to combine individual feed images from a 36-feed simulation. A mosaics is made for each set
of 36 images that has one image for each tag (param “names”) but filenames that are otherwise the same. Only the
“image” and “residual” prefixes are currently supported. For example, if the outputs produced for Data Challenge 1A
were produced for each feed and stored in a single directory, the following mosaics would be made:
image_linmos.i.clean.taylor.0, image_linmos.i.clean.taylor.0.restored, image_linmos.i.clean.taylor.1,
image_linmos.i.clean.taylor.1.restored, image_linmos.i.dirty.restored, residual_linmos.i.clean.taylor.0 and
residual_linmos.i.clean.taylor.1. Associated weights and sensitivity images would also be made, however in
situations where multiple mosaics have the same weights or sensitivites (e.g. image_linmos.i.clean.taylor.0,
image_linmos.i.clean.taylor.0.restored and residual_linmos.i.clean.taylor.0), only one would be made.
Furthermore, since the DC1A does not seem to produce weights.*.taylor.2 and we have specified weighttype
FromWeightImages, mosaic image_linmos.clean.taylor.2 would not be made. It would be produced if weighttype were
FromPrimaryBeamModel.
linmos.weighttype = FromWeightImages
linmos.findmosaics = true
linmos.names = [feed00..35_offset]